import os
import streamlit as st
import google.generativeai as gen_ai
import pyttsx3
import threading
from dotenv import load_dotenv

# Load environment variables
load_dotenv()

# Configure Streamlit page settings
st.set_page_config(
    page_title="Gemini-Pro ChatBot",
    page_icon="🤖",  # Favicon emoji
    layout="centered",  # Page layout option
)

# Retrieve Google API Key
Google_API_Key = os.getenv("Google_API_Key")

# Set up Google Gemini-Pro AI Model
gen_ai.configure(api_key=Google_API_Key)
model = gen_ai.GenerativeModel('gemini-2.0-flash')

# Function to translate roles between Gemini-Pro and Streamlit terminology
def translate_role_for_streamlit(user_role):
    return "assistant" if user_role == "model" else user_role

# Function to handle text-to-speech (TTS) in a separate thread
def speak_text(text):
    engine = pyttsx3.init()
    engine.say(text)
    engine.runAndWait()

# Initialize chat session in Streamlit if not already present
if "chat_session" not in st.session_state:
    st.session_state.chat_session = model.start_chat(history=[])

# Display chatbot title and description
st.markdown("<h1 style='text-align: center; color: #4A90E2;'>🤖 Gemini-Pro ChatBot</h1>", unsafe_allow_html=True)
st.markdown("<p style='text-align: center; font-size: 16px;'>Ask me anything! I'm powered by Gemini-Pro AI.</p>", unsafe_allow_html=True)

# Display chat history
for message in st.session_state.chat_session.history:
    with st.chat_message(translate_role_for_streamlit(message.role)):
        st.markdown(message.parts[0].text)

# User input field
user_prompt = st.chat_input("Ask Gemini Pro...")

# If user enters a prompt
if user_prompt:
    # Display user's message
    st.chat_message("user").markdown(user_prompt)

    # Show a loading indicator while waiting for a response
    with st.spinner("Thinking..."):
        gemini_response = st.session_state.chat_session.send_message(user_prompt)

    # Display Gemini-Pro's response
    with st.chat_message("assistant"):
        st.markdown(gemini_response.text)

    # Run text-to-speech in the background
    threading.Thread(target=speak_text, args=(gemini_response.text,), daemon=True).start()